Overview

Dataset statistics

Number of variables18
Number of observations2409
Missing cells1071
Missing cells (%)2.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory437.6 KiB
Average record size in memory186.0 B

Variable types

NUM13
CAT5

Reproduction

Analysis started2021-12-13 21:03:30.093032
Analysis finished2021-12-13 21:03:49.253333
Duration19.16 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

name has a high cardinality: 2304 distinct values High cardinality
style has a high cardinality: 99 distinct values High cardinality
abv has 62 (2.6%) missing values Missing
ibu has 1004 (41.7%) missing values Missing
name is uniformly distributed Uniform
id has unique values Unique
Unnamed: 0 has unique values Unique

Variables

abv
Real number (ℝ≥0)

MISSING

Distinct count74
Unique (%)3.2%
Missing62
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean0.05977758841073711
Minimum0.001
Maximum0.128
Zeros0
Zeros (%)0.0%
Memory size18.8 KiB
2021-12-13T16:03:49.291016image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum0.001
5-th percentile0.042
Q10.05
median0.056
Q30.067
95-th percentile0.087
Maximum0.128
Range0.127
Interquartile range (IQR)0.017

Descriptive statistics

Standard deviation0.01354311578
Coefficient of variation (CV)0.2265584167
Kurtosis1.143717428
Mean0.05977758841
Median Absolute Deviation (MAD)0.008
Skewness0.9578296204
Sum140.298
Variance0.0001834159851
2021-12-13T16:03:49.377398image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.052148.9%
 
0.0551586.6%
 
0.061255.2%
 
0.0651235.1%
 
0.0521074.4%
 
0.07923.8%
 
0.045893.7%
 
0.048723.0%
 
0.058662.7%
 
0.056662.7%
 
Other values (64)123551.3%
 
ValueCountFrequency (%) 
0.0011< 0.1%
 
0.02720.1%
 
0.0281< 0.1%
 
0.03230.1%
 
0.0341< 0.1%
 
ValueCountFrequency (%) 
0.1281< 0.1%
 
0.1251< 0.1%
 
0.121< 0.1%
 
0.1041< 0.1%
 
0.11< 0.1%
 

brewery_id
Real number (ℝ≥0)

Distinct count557
Unique (%)23.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean231.6766293067663
Minimum0
Maximum557
Zeros6
Zeros (%)0.2%
Memory size18.8 KiB
2021-12-13T16:03:49.470134image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11.4
Q193
median205
Q3366
95-th percentile505.6
Maximum557
Range557
Interquartile range (IQR)273

Descriptive statistics

Standard deviation157.6774235
Coefficient of variation (CV)0.6805927037
Kurtosis-1.086431747
Mean231.6766293
Median Absolute Deviation (MAD)131
Skewness0.3089630817
Sum558109
Variance24862.16989
2021-12-13T16:03:49.555033image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
10622.6%
 
25381.6%
 
166331.4%
 
141251.0%
 
46241.0%
 
80231.0%
 
131220.9%
 
368200.8%
 
165200.8%
 
107190.8%
 
Other values (547)212388.1%
 
ValueCountFrequency (%) 
060.2%
 
1130.5%
 
250.2%
 
360.2%
 
440.2%
 
ValueCountFrequency (%) 
5571< 0.1%
 
55640.2%
 
5551< 0.1%
 
5541< 0.1%
 
5531< 0.1%
 

carat
Real number (ℝ≥0)

Distinct count97
Unique (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7182689912826898
Minimum0.2
Maximum1.52
Zeros0
Zeros (%)0.0%
Memory size18.8 KiB
2021-12-13T16:03:49.643991image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.31
Q10.7
median0.72
Q30.81
95-th percentile1
Maximum1.52
Range1.32
Interquartile range (IQR)0.11

Descriptive statistics

Standard deviation0.1919936946
Coefficient of variation (CV)0.2673005475
Kurtosis1.284624277
Mean0.7182689913
Median Absolute Deviation (MAD)0.06
Skewness-0.7079764546
Sum1730.31
Variance0.03686157878
2021-12-13T16:03:49.729531image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
0.734614.4%
 
0.7127811.5%
 
0.721626.7%
 
0.91446.0%
 
0.731124.6%
 
0.321104.6%
 
0.8843.5%
 
0.75793.3%
 
0.74773.2%
 
0.77682.8%
 
Other values (87)94939.4%
 
ValueCountFrequency (%) 
0.21< 0.1%
 
0.211< 0.1%
 
0.2240.2%
 
0.23170.7%
 
0.24200.8%
 
ValueCountFrequency (%) 
1.5220.1%
 
1.520.1%
 
1.291< 0.1%
 
1.271< 0.1%
 
1.2420.1%
 

clarity
Categorical

Distinct count8
Unique (%)0.3%
Missing0
Missing (%)0.0%
Memory size18.8 KiB
SI1
624
VS2
556
VS1
420
SI2
408
VVS2
159
Other values (3)
242
ValueCountFrequency (%) 
SI162425.9%
 
VS255623.1%
 
VS142017.4%
 
SI240816.9%
 
VVS21596.6%
 
VVS11305.4%
 
I1753.1%
 
IF371.5%
 
2021-12-13T16:03:49.852600image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.073474471
Min length2

color
Categorical

Distinct count7
Unique (%)0.3%
Missing0
Missing (%)0.0%
Memory size18.8 KiB
E
572
F
444
G
428
H
332
D
316
Other values (2)
317
ValueCountFrequency (%) 
E57223.7%
 
F44418.4%
 
G42817.8%
 
H33213.8%
 
D31613.1%
 
I2179.0%
 
J1004.2%
 
2021-12-13T16:03:49.969688image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length1
Median length1
Mean length1
Min length1

cut
Categorical

Distinct count5
Unique (%)0.2%
Missing0
Missing (%)0.0%
Memory size18.8 KiB
Ideal
892
Very Good
582
Premium
563
Good
224
Fair
 
148
ValueCountFrequency (%) 
Ideal89237.0%
 
Very Good58224.2%
 
Premium56323.4%
 
Good2249.3%
 
Fair1486.1%
 
2021-12-13T16:03:50.074483image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length9
Median length5
Mean length6.279369033
Min length4

depth
Real number (ℝ≥0)

Distinct count122
Unique (%)5.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.81506849315068
Minimum53.0
Maximum69.5
Zeros0
Zeros (%)0.0%
Memory size18.8 KiB
2021-12-13T16:03:50.156211image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum53
5-th percentile59.1
Q161
median61.8
Q362.6
95-th percentile64.36
Maximum69.5
Range16.5
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.653753786
Coefficient of variation (CV)0.02675324684
Kurtosis3.123323885
Mean61.81506849
Median Absolute Deviation (MAD)0.8
Skewness0.00675001604
Sum148912.5
Variance2.734901584
2021-12-13T16:03:50.238672image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
61.81014.2%
 
61.5863.6%
 
61.6843.5%
 
62.3843.5%
 
61.3833.4%
 
61.7813.4%
 
62.1803.3%
 
62.2803.3%
 
61.9783.2%
 
62.4753.1%
 
Other values (112)157765.5%
 
ValueCountFrequency (%) 
531< 0.1%
 
53.11< 0.1%
 
53.31< 0.1%
 
551< 0.1%
 
55.120.1%
 
ValueCountFrequency (%) 
69.51< 0.1%
 
69.320.1%
 
68.51< 0.1%
 
68.31< 0.1%
 
68.220.1%
 

ibu
Real number (ℝ≥0)

MISSING

Distinct count107
Unique (%)7.6%
Missing1004
Missing (%)41.7%
Infinite0
Infinite (%)0.0%
Mean42.71316725978647
Minimum4.0
Maximum138.0
Zeros0
Zeros (%)0.0%
Memory size18.8 KiB
2021-12-13T16:03:50.331229image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile11
Q121
median35
Q364
95-th percentile92
Maximum138
Range134
Interquartile range (IQR)43

Descriptive statistics

Standard deviation25.95406591
Coefficient of variation (CV)0.6076361829
Kurtosis-0.1357120402
Mean42.71316726
Median Absolute Deviation (MAD)17
Skewness0.7925208569
Sum60012
Variance673.6135373
2021-12-13T16:03:50.417322image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
20823.4%
 
35602.5%
 
65542.2%
 
30532.2%
 
70482.0%
 
18461.9%
 
25451.9%
 
60441.8%
 
40411.7%
 
15401.7%
 
Other values (97)89237.0%
 
(Missing)100441.7%
 
ValueCountFrequency (%) 
430.1%
 
550.2%
 
630.1%
 
770.3%
 
890.4%
 
ValueCountFrequency (%) 
1381< 0.1%
 
1351< 0.1%
 
1301< 0.1%
 
1261< 0.1%
 
12030.1%
 

id
Real number (ℝ≥0)

UNIQUE

Distinct count2409
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1431.1112494811125
Minimum1
Maximum2692
Zeros0
Zeros (%)0.0%
Memory size18.8 KiB
2021-12-13T16:03:50.509983image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile135
Q1808
median1454
Q32076
95-th percentile2568.6
Maximum2692
Range2691
Interquartile range (IQR)1268

Descriptive statistics

Standard deviation752.6161934
Coefficient of variation (CV)0.5258963576
Kurtosis-1.087838414
Mean1431.111249
Median Absolute Deviation (MAD)631
Skewness-0.1212128728
Sum3447547
Variance566431.1346
2021-12-13T16:03:50.592957image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
20471< 0.1%
 
12241< 0.1%
 
12201< 0.1%
 
12181< 0.1%
 
12141< 0.1%
 
12121< 0.1%
 
12101< 0.1%
 
12081< 0.1%
 
12061< 0.1%
 
12041< 0.1%
 
Other values (2399)239999.6%
 
ValueCountFrequency (%) 
11< 0.1%
 
41< 0.1%
 
51< 0.1%
 
61< 0.1%
 
71< 0.1%
 
ValueCountFrequency (%) 
26921< 0.1%
 
26911< 0.1%
 
26901< 0.1%
 
26891< 0.1%
 
26881< 0.1%
 

name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct count2304
Unique (%)95.6%
Missing0
Missing (%)0.0%
Memory size18.8 KiB
Nonstop Hef Hop
 
12
Dale's Pale Ale
 
6
Oktoberfest
 
6
Longboard Island Lager
 
4
1327 Pod's ESB
 
3
Other values (2299)
2378
ValueCountFrequency (%) 
Nonstop Hef Hop120.5%
 
Dale's Pale Ale60.2%
 
Oktoberfest60.2%
 
Longboard Island Lager40.2%
 
1327 Pod's ESB30.1%
 
Dagger Falls IPA30.1%
 
Boston Lager30.1%
 
Bombshell Blonde20.1%
 
Halcyon Unfiltered Wheat20.1%
 
#920.1%
 
Other values (2294)236698.2%
 
2021-12-13T16:03:50.705623image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length52
Median length16
Mean length17.2988792
Min length2

ounces
Real number (ℝ≥0)

Distinct count7
Unique (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.592901618929016
Minimum8.4
Maximum32.0
Zeros0
Zeros (%)0.0%
Memory size18.8 KiB
2021-12-13T16:03:50.793520image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum8.4
5-th percentile12
Q112
median12
Q316
95-th percentile16
Maximum32
Range23.6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.352468187
Coefficient of variation (CV)0.1730659319
Kurtosis9.037233846
Mean13.59290162
Median Absolute Deviation (MAD)0
Skewness2.046132674
Sum32745.3
Variance5.534106569
2021-12-13T16:03:50.874753image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
12152463.3%
 
1684134.9%
 
24220.9%
 
19.2150.6%
 
3250.2%
 
16.91< 0.1%
 
8.41< 0.1%
 
ValueCountFrequency (%) 
8.41< 0.1%
 
12152463.3%
 
1684134.9%
 
16.91< 0.1%
 
19.2150.6%
 
ValueCountFrequency (%) 
3250.2%
 
24220.9%
 
19.2150.6%
 
16.91< 0.1%
 
1684134.9%
 

price
Real number (ℝ≥0)

Distinct count441
Unique (%)18.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2649.266085512661
Minimum326
Maximum3179
Zeros0
Zeros (%)0.0%
Memory size18.8 KiB
2021-12-13T16:03:50.961052image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum326
5-th percentile556
Q12812
median2909
Q33040
95-th percentile3152.6
Maximum3179
Range2853
Interquartile range (IQR)228

Descriptive statistics

Standard deviation811.2885808
Coefficient of variation (CV)0.3062314447
Kurtosis2.989353276
Mean2649.266086
Median Absolute Deviation (MAD)108
Skewness-2.19025434
Sum6382082
Variance658189.1613
2021-12-13T16:03:51.042204image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
561913.8%
 
554341.4%
 
558321.3%
 
2822231.0%
 
557210.9%
 
2777210.9%
 
3084190.8%
 
559180.7%
 
3105170.7%
 
3145170.7%
 
Other values (431)211687.8%
 
ValueCountFrequency (%) 
32620.1%
 
3271< 0.1%
 
3341< 0.1%
 
3351< 0.1%
 
33620.1%
 
ValueCountFrequency (%) 
317930.1%
 
317820.1%
 
317720.1%
 
317650.2%
 
317590.4%
 

style
Categorical

HIGH CARDINALITY

Distinct count99
Unique (%)4.1%
Missing5
Missing (%)0.2%
Memory size18.8 KiB
American IPA
424
American Pale Ale (APA)
 
245
American Amber / Red Ale
 
133
American Blonde Ale
 
108
American Double / Imperial IPA
 
105
Other values (94)
1389
ValueCountFrequency (%) 
American IPA42417.6%
 
American Pale Ale (APA)24510.2%
 
American Amber / Red Ale1335.5%
 
American Blonde Ale1084.5%
 
American Double / Imperial IPA1054.4%
 
American Pale Wheat Ale974.0%
 
American Brown Ale702.9%
 
American Porter682.8%
 
Saison / Farmhouse Ale522.2%
 
Witbier512.1%
 
Other values (89)105143.6%
 
2021-12-13T16:03:51.152964image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Length

Max length35
Median length18
Mean length17.2407638
Min length3

table
Real number (ℝ≥0)

Distinct count45
Unique (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.58588625985886
Minimum51.0
Maximum70.0
Zeros0
Zeros (%)0.0%
Memory size18.8 KiB
2021-12-13T16:03:51.238265image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum51
5-th percentile54
Q156
median57
Q359
95-th percentile62
Maximum70
Range19
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.363736636
Coefficient of variation (CV)0.04104715217
Kurtosis1.903035993
Mean57.58588626
Median Absolute Deviation (MAD)1
Skewness0.9410429347
Sum138724.4
Variance5.587250886
2021-12-13T16:03:51.323002image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
5746319.2%
 
5643117.9%
 
5835814.9%
 
5927911.6%
 
5526411.0%
 
602058.5%
 
541064.4%
 
611014.2%
 
62662.7%
 
63351.5%
 
Other values (35)1014.2%
 
ValueCountFrequency (%) 
511< 0.1%
 
5230.1%
 
53251.0%
 
53.620.1%
 
53.720.1%
 
ValueCountFrequency (%) 
7020.1%
 
6920.1%
 
681< 0.1%
 
6770.3%
 
6690.4%
 

Unnamed: 0
Real number (ℝ≥0)

UNIQUE

Distinct count2409
Unique (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1205.0
Minimum1
Maximum2409
Zeros0
Zeros (%)0.0%
Memory size18.8 KiB
2021-12-13T16:03:51.417206image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile121.4
Q1603
median1205
Q31807
95-th percentile2288.6
Maximum2409
Range2408
Interquartile range (IQR)1204

Descriptive statistics

Standard deviation695.5627218
Coefficient of variation (CV)0.5772304745
Kurtosis-1.2
Mean1205
Median Absolute Deviation (MAD)602
Skewness0
Sum2902845
Variance483807.5
2021-12-13T16:03:51.494984image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
20471< 0.1%
 
12561< 0.1%
 
12521< 0.1%
 
12501< 0.1%
 
12481< 0.1%
 
12461< 0.1%
 
12441< 0.1%
 
12421< 0.1%
 
12401< 0.1%
 
12381< 0.1%
 
Other values (2399)239999.6%
 
ValueCountFrequency (%) 
11< 0.1%
 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
51< 0.1%
 
ValueCountFrequency (%) 
24091< 0.1%
 
24081< 0.1%
 
24071< 0.1%
 
24061< 0.1%
 
24051< 0.1%
 

x
Real number (ℝ≥0)

Distinct count245
Unique (%)10.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.683864674138647
Minimum3.79
Maximum7.53
Zeros0
Zeros (%)0.0%
Memory size18.8 KiB
2021-12-13T16:03:51.579028image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum3.79
5-th percentile4.33
Q15.67
median5.79
Q35.98
95-th percentile6.386
Maximum7.53
Range3.74
Interquartile range (IQR)0.31

Descriptive statistics

Standard deviation0.5870836051
Coefficient of variation (CV)0.1032895114
Kurtosis1.81348931
Mean5.683864674
Median Absolute Deviation (MAD)0.15
Skewness-1.406857999
Sum13692.43
Variance0.3446671594
2021-12-13T16:03:51.662776image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
5.73612.5%
 
5.7542.2%
 
5.69522.2%
 
5.74512.1%
 
5.71512.1%
 
5.76512.1%
 
5.79512.1%
 
5.8502.1%
 
5.75482.0%
 
5.72472.0%
 
Other values (235)189378.6%
 
ValueCountFrequency (%) 
3.791< 0.1%
 
3.831< 0.1%
 
3.851< 0.1%
 
3.871< 0.1%
 
3.881< 0.1%
 
ValueCountFrequency (%) 
7.5320.1%
 
7.261< 0.1%
 
7.121< 0.1%
 
7.011< 0.1%
 
6.991< 0.1%
 

y
Real number (ℝ≥0)

Distinct count244
Unique (%)10.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.683416355334163
Minimum3.75
Maximum7.42
Zeros0
Zeros (%)0.0%
Memory size18.8 KiB
2021-12-13T16:03:51.754035image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum3.75
5-th percentile4.34
Q15.68
median5.8
Q35.97
95-th percentile6.33
Maximum7.42
Range3.67
Interquartile range (IQR)0.29

Descriptive statistics

Standard deviation0.5753570982
Coefficient of variation (CV)0.1012343742
Kurtosis1.931271285
Mean5.683416355
Median Absolute Deviation (MAD)0.15
Skewness-1.49531877
Sum13691.35
Variance0.3310357904
2021-12-13T16:03:51.837819image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
5.75702.9%
 
5.73622.6%
 
5.76572.4%
 
5.7562.3%
 
5.74522.2%
 
5.72522.2%
 
5.77502.1%
 
5.81502.1%
 
5.8461.9%
 
5.85451.9%
 
Other values (234)186977.6%
 
ValueCountFrequency (%) 
3.751< 0.1%
 
3.781< 0.1%
 
3.8420.1%
 
3.851< 0.1%
 
3.881< 0.1%
 
ValueCountFrequency (%) 
7.4220.1%
 
7.091< 0.1%
 
7.051< 0.1%
 
6.951< 0.1%
 
6.921< 0.1%
 

z
Real number (ℝ≥0)

Distinct count176
Unique (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5101909506019093
Minimum0.0
Maximum4.78
Zeros2
Zeros (%)0.1%
Memory size18.8 KiB
2021-12-13T16:03:51.929419image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2.68
Q13.49
median3.57
Q33.7
95-th percentile3.986
Maximum4.78
Range4.78
Interquartile range (IQR)0.21

Descriptive statistics

Standard deviation0.3833005553
Coefficient of variation (CV)0.1091964969
Kurtosis6.831866423
Mean3.510190951
Median Absolute Deviation (MAD)0.1
Skewness-1.755561391
Sum8456.05
Variance0.1469193157
2021-12-13T16:03:52.011194image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
3.54964.0%
 
3.56913.8%
 
3.53863.6%
 
3.55863.6%
 
3.57863.6%
 
3.58833.4%
 
3.52773.2%
 
3.59702.9%
 
3.51552.3%
 
3.6542.2%
 
Other values (166)162567.5%
 
ValueCountFrequency (%) 
020.1%
 
2.271< 0.1%
 
2.3130.1%
 
2.331< 0.1%
 
2.371< 0.1%
 
ValueCountFrequency (%) 
4.781< 0.1%
 
4.71< 0.1%
 
4.421< 0.1%
 
4.381< 0.1%
 
4.341< 0.1%
 

Interactions

2021-12-13T16:03:30.319882image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:30.441771image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:30.548052image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:30.652244image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:30.761138image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:30.860613image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:30.961530image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:31.060062image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:31.161438image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:31.276391image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:31.378299image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:31.482992image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:31.590072image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:31.687771image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:31.787849image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:31.883188image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:31.980454image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:32.082460image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:32.182535image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:32.278680image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:32.370970image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:32.468344image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:32.569438image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:32.665119image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:33.202977image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:33.310602image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:33.404562image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:33.509014image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:33.608667image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:33.709977image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:33.814957image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:33.917734image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:34.017275image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:34.114882image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:34.214816image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:34.321436image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:34.423387image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:34.526731image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:34.632623image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:34.730984image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:34.836533image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:34.941266image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:35.048333image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:35.157058image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:35.265372image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:35.368996image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:35.469523image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:35.573386image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:35.683349image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:35.787581image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:35.895884image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:36.003970image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:36.106904image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:36.207054image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:36.308466image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:36.411751image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:36.518972image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:36.624863image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:36.724855image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:36.940459image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:37.055919image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:37.163082image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:37.265562image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:37.371544image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:37.477565image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:37.577494image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:37.675437image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:37.770910image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:37.868540image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:37.968180image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:38.066003image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:38.159977image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:38.252707image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:38.348141image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:38.450474image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:38.545996image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:38.646764image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:38.746758image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:38.841575image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:38.936183image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:39.028190image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:39.122344image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:39.221039image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:39.317685image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:39.409468image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:39.499976image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:39.592495image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:39.692371image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:39.785719image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:39.882925image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:39.981806image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:40.072233image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:40.171782image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:40.270401image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:40.374801image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:40.475757image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:40.575822image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:40.670175image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:40.765528image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:40.861391image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:40.963124image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:41.059075image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:41.158446image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:41.406335image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:41.517412image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:41.624699image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:41.730021image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:41.837488image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:41.947562image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:42.054348image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:42.161766image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:42.266297image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:42.370064image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:42.479135image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:42.582516image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:42.689268image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:42.796954image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:42.905599image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:43.004643image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:43.100690image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:43.200889image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:43.302603image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:43.403669image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:43.498487image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:43.591765image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:43.688743image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:43.788835image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:43.884204image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:43.984394image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:44.083659image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:44.176651image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:44.281991image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:44.385479image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:44.492227image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:44.603047image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:44.710634image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:44.814048image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:44.916111image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:45.020784image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:45.130882image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:45.234442image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:45.342597image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:45.450576image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:45.551407image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:45.658323image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:45.761684image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:45.866783image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:45.976329image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:46.081643image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:46.183447image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:46.285061image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:46.387899image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:46.497389image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:46.684314image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:46.826800image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:46.971625image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:47.285432image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:47.423597image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:47.550736image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:47.682004image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:47.822343image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:47.954341image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:48.076641image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:48.169882image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:48.263940image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:48.364302image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:48.459505image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:48.559456image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:48.658771image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Missing values

2021-12-13T16:03:48.865458image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/
2021-12-13T16:03:49.150493image/svg+xmlMatplotlib v3.3.0, https://matplotlib.org/

Sample

First rows

Unnamed: 0caratcutcolorclaritydepthtablepricexyzabvibuidnamestylebrewery_idounces
010.23IdealESI261.555.03263.953.982.430.066NaN2265Devil's CupAmerican Pale Ale (APA)17712.0
120.21PremiumESI159.861.03263.893.842.310.071NaN2264Rise of the PhoenixAmerican IPA17712.0
230.23GoodEVS156.965.03274.054.072.310.090NaN2263SinisterAmerican Double / Imperial IPA17712.0
340.29PremiumIVS262.458.03344.204.232.630.075NaN2262Sex and CandyAmerican IPA17712.0
450.31GoodJSI263.358.03354.344.352.750.077NaN2261Black ExodusOatmeal Stout17712.0
560.24Very GoodJVVS262.857.03363.943.962.480.045NaN2260Lake Street ExpressAmerican Pale Ale (APA)17712.0
670.24Very GoodIVVS162.357.03363.953.982.470.065NaN2259ForemanAmerican Porter17712.0
780.26Very GoodHSI161.955.03374.074.112.530.055NaN2258JadeAmerican Pale Ale (APA)17712.0
890.22FairEVS265.161.03373.873.782.490.086NaN2131Cone CrusherAmerican Double / Imperial IPA17712.0
9100.23Very GoodHVS159.461.03384.004.052.390.072NaN2099Sophomoric SaisonSaison / Farmhouse Ale17712.0

Last rows

Unnamed: 0caratcutcolorclaritydepthtablepricexyzabvibuidnamestylebrewery_idounces
239924000.31IdealGVS261.755.05624.374.392.700.06050.01511Worthy PaleAmerican Pale Ale (APA)19912.0
240024010.70IdealEVS261.156.031765.735.763.510.042NaN1345Patty's Chile BeerChile Beer42412.0
240124020.72IdealDSI260.557.031765.825.893.540.082NaN1316Colorojo Imperial Red AleAmerican Strong Ale42412.0
240224030.70Very GoodEVS163.857.031775.615.653.590.055NaN1045Wynkoop Pumpkin AlePumpkin Ale42412.0
240324040.74IdealDVS261.154.031775.865.893.590.075NaN1035Rocky Mountain Oyster StoutAmerican Stout42412.0
240424050.67Very GoodGVVS162.056.031785.605.623.480.06745.0928BelgoradoBelgian IPA42412.0
240524060.74IdealHVS262.255.031785.835.813.620.052NaN807Rail Yard AleAmerican Amber / Red Ale42412.0
240624070.72IdealGVVS262.656.031795.705.743.580.055NaN620B3K Black LagerSchwarzbier42412.0
240724080.72IdealDVS260.856.031795.805.843.540.05540.0145Silverback Pale AleAmerican Pale Ale (APA)42412.0
240824090.72IdealDVS262.157.031795.695.753.550.052NaN84Rail Yard Ale (2009)American Amber / Red Ale42412.0